Automated tool data generation in automated asset management systems

ABSTRACT

An asset management system automatically generates and updates tool data stored in and used by the system for determining the presence or absence of tools or other inventory objects in the systems. The tool data can be automatically generated when a tool is newly added to the automated asset management system, and can be updated if and when characteristics of the tool and/or automated asset management system change. The automatic generation and updating includes automatically recognizing unique identifiers of tags located on inventory objects, automatically identifying an inventory object to associate with each unique identifier, and automatically populating a database to store each unique identifier in association with stored data for the corresponding inventory object.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No.62/458,191, filed on Feb. 13, 2017, in the U.S. Patent and TrademarkOffice, the disclosure of which is incorporated by reference herein inits entirety.

TECHNICAL FIELD

The present subject matter relates to automated tool control systems,and to techniques and equipment to automatically generate and update adatabase of tool data for use in tracking tools stored in automated toolcontrol systems.

BACKGROUND

When tools are used in a manufacturing or service environment, it isimportant that the tools be returned to a storage unit, such as a toolbox, tool locker, or secure enclosed area (e.g., tool crib, tool room,tool closet, or walk in tool locker) after use. Some industries havehigh standards for inventory control of tools, for example to preventincidents of leaving tools in the workplace environment where they couldcause severe damages. In the aerospace industry, for instance, it isimportant to ensure that no tools are accidentally left behind in anaircraft or missile being manufactured, assembled, or repaired in orderto prevent foreign object damage (FOD) to the aircraft.

Some toolboxes include built-in inventory determination features totrack inventory conditions of tools stored in those toolboxes. Forexample, some toolboxes dispose contact sensors, magnetic sensors, orinfrared sensors in or next to all tool storage locations to detectwhether a tool is placed in each tool storage location. Based on signalsgenerated by the sensors, the toolboxes are able to determine whetherany tools are missing.

In toolboxes having built-in inventory determination features, theinventory conditions of tools are determined based on informationreceived from sensors as well stored tool data. For example, aninventory condition of a particular tool can be determined bydetermining whether the information received from the sensors matchesthe stored tool data.

In order to provide accurate and up-to-date inventory information, thetool data needs to be generated and updated as tools, sensors, and thetools' sensed characteristics change. A need therefore exists forautomated tool data generation and updating in asset management systemsto provide accurate and up-to-date inventory information.

SUMMARY

The teachings herein alleviate one or more of the above noted problemsby providing systems and method for automatically recognizing andstoring in a database unique identifier encoded on tags of inventoryobjects for use in inventory control.

In accordance with one aspect of the disclosure, an automated assetmanagement system includes a plurality of storage locations for storingobjects, an image-based sensing system configured to generate imagesused to determine presence or absence of objects configured to be storedin the plurality of storage locations, a database storing data relatingto the objects configured to be stored in the plurality of storagelocations, a processor, and a non-transitory machine readable recordingmedium storing program instructions. The database stores data sufficientto enable the asset management system to determine the presence orabsence of the objects from the storage locations based on the imagesgenerated by the image-based sensing system. The stored programinstructions, when executed by the processor, cause the processor toperform a tool training process for automatically storing in thedatabase a unique identifier encoded on a tag of an object. Inparticular, the processor performs using the image-based sensing systema first scan of the storage locations while a particular storagelocation associated with a particular object subject to the tooltraining is empty, and stores an image attribute of the particularstorage location while the particular storage location is empty. Theprocessor further performs using the image-based sensing system a secondscan of the storage locations while the particular storage locationassociated with the particular object subject to the tool training isoccupied by the particular object, and stores an image attribute of theparticular storage location while the particular object is present. Theprocessor determines, based on an image captured during the second scan,whether a tag encoding a unique identifier is present on the particularobject, and updates the database storing data relating to the objectsconfigured to be stored in the plurality of storage locations of theasset management system to include, in association with stored datarelating to the particular object, the unique identifier of the tagdetermined to be present on the particular object.

In accordance with another aspect of the disclosure, a method isprovided for automatically storing, in a database of an automated assetmanagement system having a plurality of storage locations for storingobjects, a unique identifier encoded on a tag of an object. The methodincludes performing, using an image-based sensing system configured togenerate images used to determine presence or absence of objectsconfigured to be stored in the plurality of storage locations of theasset management system, a first scan of the plurality of storagelocations while a particular storage location associated with aparticular object subject to tool training is empty. An image attributeof the particular storage location while the particular storage locationis empty is stored in the database. The method performs, using theimage-based sensing system, a second scan of the storage locations whilethe particular storage location associated with the particular objectsubject to the tool training is occupied by the particular object. Animage attribute of the particular storage location while the particularobject is present is stored in the database. The method determines,based on an image generated by the image-based sensing system during thesecond scan, whether a tag encoding a unique identifier is present onthe particular object. The database of the asset management systemstoring data relating to the objects configured to be stored in theplurality of storage locations is updated to include, in associationwith stored data relating to the particular object, the uniqueidentifier of the tag determined to be present on the particular object.The image attributes stored in the database are sufficient to enable theasset management system to determine the presence or absence of theobjects from the storage locations based on the images generated by theimage-based sensing system.

Additional advantages and novel features will be set forth in part inthe description which follows, and in part will become apparent to thoseskilled in the art upon examination of the following and theaccompanying drawings or may be learned by production or operation ofthe examples. The advantages of the present teachings may be realizedand attained by practice or use of various aspects of the methodologies,instrumentalities and combinations set forth in the detailed examplesdiscussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawing figures depict one or more implementations in accord withthe present teachings, by way of example only, not by way of limitation.In the figures, like reference numerals refer to the same or similarelements.

FIGS. 1A-1D show illustrative automated asset management systems in theform of tool storage systems that support functionality forautomatically recognizing and storing tag data from inventory object.

FIG. 2 shows a detailed view of one drawer of an automated tool storagesystem like those shown in FIGS. 1A-1C in an open position.

FIG. 3 shows a perspective view of an imaging system in an automatedtool storage system like those shown in FIGS. 1A-1C.

FIGS. 4A-4C show examples of tags that can be placed on tools or storageobjects to encode unique identifiers and to be automatically recognizedby an automated tool storage system like those shown in FIGS. 1A-1C.

FIG. 5 is a simplified block diagram showing steps of a method for tooltraining including automatically recognizing and storing tag data frominventory object.

FIGS. 6 and 7 are simplified functional block diagrams of computers thatmay be configured to function as tool storage systems or as a hosts orservers supporting functions of the tool storage system.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant teachings. However, it should be apparent to those skilledin the art that the present teachings may be practiced without suchdetails. In other instances, well known methods, procedures, components,and/or circuitry have been described at a relatively high-level, withoutdetail, in order to avoid unnecessarily obscuring aspects of the presentteachings.

The various methods and systems disclosed herein relate to the automatedgeneration and updating of tool data stored in and used by automatedasset management systems for determining the presence or absence oftools in such systems. The tool data may be generated when a tool isnewly added to the automated asset management systems, and may beupdated if and when characteristics of the tool and/or automated assetmanagement system change.

In one example, an automated asset management system stores tool datafor each of the tools whose inventory can be automatically monitored bythe system. The tool data can include data on characteristics of toolsto be stored in the system and/or data on characteristics of storagelocations for tools in the system. When a new tool is to be stored inthe system, or when a characteristic of a tool changes, a user canactivate a tool training mode on the system. The tool training mode isused to generate and/or update the tool data stored by the automatedasset management system based on characteristics of the tool sensedduring a tool training procedure.

The tool training procedure can be used, for example, in situations inwhich tools have tags encoding unique identifiers affixed thereto. Insuch situations, the training procedure can be used following attachmentof a tag to a tool to be stored in the automated asset system. Byactivating the tool training mode, the automated asset system is causedto conduct a silhouette training with no objects in the drawers, conducta tool absence training to record color attributes of the empty storagelocations, and to conduct tool presence training with the tool (and,optionally, a tag on the tool) in an associated storage location. Thetool presence training can include scanning the storage locationsmultiple times (e.g., three times, or more) to record color, shape,and/or other attributes of the storage location with the tool present.If a tag is determined to be present on the tool during the toolpresence training, the system recognizes the tag, validates the tag, andcreates an association in a database of tool data associating theidentified code provided on the tag with the tool's object datapreviously entered in the database. The tag data is initially stored inthe automated asset system database and can then be copied to a serverdatabase.

Reference now is made in detail to the examples illustrated in theaccompanying drawings and discussed below.

FIGS. 1A-1D show various illustrative automated asset management systems(or inventory control systems) in the form of tool storage systems 300.While the tool storage systems 300 shown in FIGS. 1A-1C are toolboxes,the tool storage systems 300 may more generally be tool lockers or anyother secure storage devices or enclosed secure storage areas (e.g., atool crib or walk-in tool locker).

Each tool storage system 300 is an example of a highly automatedinventory control system that utilizes a single or multiple differentsensing technologies for identifying inventory conditions of objects inthe storage unit. In one example, the tool storage system 300 uses amachine imaging sensing methodology for identifying inventory conditionsof objects in the storage unit. In another example, the system 300 usesa radio-frequency (RF) sensing technology for identifying the inventoryconditions. In further examples, the system 300 uses both machineimaging sensing and RF sending technologies for identifying theinventory conditions.

More detailed information on the tool storage system 300 can be found inU.S. Pat. No. 9,041,508, entitled IMAGE-BASED INVENTORY CONTROL SYSTEMAND METHOD and issued on May 26, 2015, 2009; in U.S. Pat. No. 8,842,183,entitled IMAGE-BASED INVENTORY CONTROL SYSTEM WITH AUTOMATIC CALIBRATIONAND IMAGE CORRECTION and issued Sep. 23, 2014; and in U.S. Pat. No.9,741,014, entitled AUTOMATED ASSET MANAGEMENT SYSTEM WITH MULTIPLESENSING TECHNOLOGIES and issued Aug. 22, 2017, which are herebyincorporated by reference in their entireties.

As shown in each of FIGS. 1A-1C, the tool storage system 300 includes auser interface 305, an access control device 306, such as a card reader,for verifying identity and authorization levels of a user intending toaccess storage system 300, and multiple tool storage drawers 330 forstoring tools. Instead of drawers 330, the storage system may includeshelves, compartments, containers, or other object storage devices fromwhich tools or objects are issued and/or returned, or which contain thestorage device from which the objects are issued and/or returned. Infurther examples, the storage system includes storage hooks, hangers,toolboxes with drawers, lockers, cabinets with shelves, safes, boxes,closets, vending machines, barrels, crates, and other material storagemeans.

User interface 305 is an input and/or output device of storage system330 that is configured to receive and/or display information from/to auser. Access control device 306 is used to limit or allow access to toolstorage drawers 330, based for example on authenticating a user'sidentity. Access control device 306, through the use of one or moreelectronically controlled locking devices or mechanisms, keeps some orall storage drawers 330 locked in a closed position until access controldevice 306 authenticates a user's authorization for accessing storagesystem 300. The access control device 306 further includes a processorand software to electronically identify a user requesting access to thesecure area or object storage device. If access control device 306determines that a user is authorized to access storage system 300, itunlocks some or all storage drawers 330, depending on the user'sauthorization level, allowing the user to remove or replace tools. Inparticular, the access control device 306 may identify predeterminedauthorized access levels to the system for different users, and allow ordeny physical access by the user to the three dimensional space orobject storage devices based on the predetermined authorized level ofaccess for the identified user.

Tool storage system 300 can rely on various different sensing systemsfor operation. In an illustrative example shown in FIG. 1D, the toolstorage system 300 includes an image-based sensing system 351 configuredto capture images of contents or storage locations of the system. Theimage-based sensing system 351 may include lens-based cameras, CCDcameras, CMOS cameras, video cameras, or any type of device thatcaptures images. The tool storage system 300 can alternatively oradditionally include an RF-based sensing system 353 including one ormore RFID antennas, RFID transceivers, and RFID processors, as furthershown in FIG. 1D. The RF-based sensing system is configured to emit RFsensing signals, receive RFID signals returned from RFID tags mounted onor incorporated in tools or other inventory items in response to the RFsensing signals, and process the received RFID signals to identifyindividual tools or inventory items. Specifically, the received RFIDsignals may be processed to extract tag identification data included inthe returned RFID signals, and to identify individual tools or inventoryitems based on an association between tag identification data and tooldata stored by the system.

The image-based sensing system is described in further detail below inrelation to FIG. 3. While FIG. 3 corresponds to the specific embodimentof the storage system 300 shown in FIGS. 1C and 1D, the teachingsillustrated in FIG. 3 can be applied to each of the embodiments of FIGS.1A-1C. The RFID sensing system may be configured to sense RFID tags oftools located in all storage drawers 330 of system 300, or configured tosense RFID tags of tools located in a particular subset of the drawers330 of system 300. In one example, the RFID sensing system is configuredto sense RFID tags of tools located only in the top-most and bottom-mostdrawers 330 of system 300, and the RFID sensing system includes RFIDantennas disposed directly above the top-most and bottom-most drawers330 within system 300 to sense RFID tags of tools located in thosedrawers. Other configurations of RFID antennas can also be used.

System 300 further includes a data processing system 355, such as acomputer, for processing images captured by the image sensing device,for processing RF signals captured by the RFID antennas andtransceivers, and/or for processing other sensing signals received byother sensing systems. The data processing system 355 includes one ormore processors (e.g., micro-processors) and memory storing programinstructions for causing the tool storage system 300 to communicateelectronically directly or through a network with sensing devices andobtain data from sensing devices relative to the presence or absencestatus of objects within the three dimensional space or object storagedevice. Images, RFID signals, and other sensing signals captured orreceived by the sensing systems are processed by the data processingsystem 355 for determining an inventory condition of the system or eachstorage drawer. The term inventory condition as used throughout thisdisclosure means information relating to an existence/presence ornon-existence/absence condition of objects in the storage system.

System 300 further includes a database 357 stored in non-transitorymemory that is communicatively connected to the data processing system.In general, the database 357 is at least partially stored in memorylocal to the tool storage system 300 (e.g., operative memory of the toolstorage system 300), although in some embodiments the database can bestored (or duplicated) on a server or other memory remote from the toolstorage system 200. The database 357 stores tool data used by the dataprocessing system 355 to determine the inventory conditions of tools orother objects stored in the tool storage system 300. The tool data caninclude data identifying each tool known to the tool storage system 300including information such as a common tool name (e.g., “socket wrench)and/or a unique tool identifier (e.g., a serial number or otheridentifier). The tool data generally also includes information onstorage location(s) for the tool in the tool storage system 300. Thetool data further includes sensing data, such as data used to determinewhether the tool is present in or absent from the tool storage system300 based on the data received from sensors of the tool storage system300. The sensing data can include an RFID identifier in cases in whichan RFID sensing system is used, a numerical or barcode identifier incases in which a barcode sensing system or other tag-based sensingsystem is used, image data or image-related data in cases in which animage-based sensing system is used, or the like. For example, in thecase of image-based sensing systems, the sensing data can include imagedata (e.g., a stored image of the tool, of a storage location for thetool in which the tool is present, and/or of a storage location for thetool in which the tool is absent) or image-related data enabling thesystem to determine presence or absence of the tool (e.g., attributes ofimages in which the tool is or is not present on the basis of which thesystem can determine presence or absence of the tool). The stored tooldata, in combination with sensing data received from the sensingsubsystem, is generally sufficient to enable the system 300 to determinepresence or absence of the tools for which data is stored.

The data processing system 355 may be part of tool storage system 300.Alternatively, the data processing system 355 can be implemented atleast in part on a remote computer or server 361 having a data link,such as a wired or wireless link, coupled to tool storage system 300, ora combination of a computer integrated in storage system 300 and acomputer remote from storage system 300. Additionally, the dataprocessing system 355 can be connected to a computer network andexchange data with an administrative software application (e.g., as maybe executed on a server) used to manipulate and store data and store anddisplay information relative to the data to system users. For purposesof communicating with the remote computer or server 361, the toolstorage system 300 generally includes a network communication interface359 that can support wired or wireless communications with remotecomputers or servers through direct data links or communicationnetworks.

FIG. 2 shows a detailed view of one drawer 330 of the storage system 300in an open position. Each storage drawer 300 includes a foam base 180having a plurality of storage locations, such as tool cutouts 181, forstoring tools. Each cutout is specifically contoured and shaped forfittingly receiving tools with corresponding shapes. Tools may besecured in each storage location by using hooks, Velcro, latches,pressure from the foam, etc. The foam base 180 can include additionalholes or channels (not shown in FIG. 2) that are contiguous with thetool cutouts 181 and are designed to enable users' fingers to graspobjects or tools stored in the tool cutouts 181. In general, theadditional holes or channels are positioned and shaped such that thetool cutouts 181 secure and immobilize the objects and tools in thestorage system 300 despite the presence of the holes or channels.

In general, each storage drawer 330 includes multiple storage locationsfor storing various types of tools. As used throughout this disclosure,a storage location is a location in a storage system for storing orsecuring objects. In one embodiment, each tool has a specificpre-designated storage location in the tool storage system. In otherembodiments, multiple tools can share one or more storage locations suchthat, for example, multiple identical wrenches can be stored in any of aset of storage locations that are configured (e.g., shaped) andpre-designated to store such identical wrenches. Further, one or moretools in the drawer 330 may have an RFID tag or other tag mounted orattached thereon.

FIG. 3 shows a perspective view of an imaging system in tool storagesystem 300. As illustrated in FIG. 3, storage system 300 includes animaging compartment 315 which houses an image sensing system comprisingthree cameras 310 and a light directing device, such as a mirror 312having a reflection surface disposed at about 45 degrees downwardlyrelative to a vertical surface, for directing light reflected fromdrawers 330 to cameras 310. The directed light, after arriving atcameras 310, allows cameras 310 to form images of drawers 330. Theshaded area 340 below mirror 312 represents a viewing field of theimaging sensing system of tool storage system 300. As shown at 340, theimaging system scans a portion of an open drawer 336 that passes throughthe field of view of the imaging sensing system, for example as thedrawer 336 is opened and/or closed. The imaging system thereby capturesan image of at least that portion of the drawer 336 that was opened.Processing of the captured image is used to determine the inventoryconditions of tools and/or storage locations in the portion of thedrawer 336 that was opened.

In general, the image sensing system captures an image of a particulardrawer 330 and performs an inventory of the drawer in response todetecting movement of the particular drawer. For example, the imagesensing system may perform an inventory of the drawer in response todetecting that the drawer is closing or has become completely closed. Inother examples, the image sensing system may image the drawer both as itis opening and as it is closing.

The RF sensing system is generally configured to perform inventorychecks of drawers having RF-based tags associated therewith. TheRF-based tags may be RFID tags that are attached to or embedded withinthe tools. In general, the RF-based tag encodes an identifier unique tothe tool, such that both the tool type (e.g., screwdriver, torquewrench, or the like) and the unique tool (e.g., a particular torquewrench, from among a plurality of torque wrenches of the same model andtype) can be identified from reading the RF-based tag. In particular,the information encoded in the RF-based tag is generally unique to thetool such that it can be used to distinguish between two tools that areof a same type, same model, same age, same physical appearance, etc.

The RF sensing system includes antennas mounted in or around the toolstorage system 300. Each antenna is coupled to an RF transceiver that isoperative to cause the antenna to emit an RF sensing signal used toexcite the RF-based tags located within the vicinity of the antenna, andis operative to sense RF identification signals returned by the RF-basedtags in response to the RF sensing signal. One or more RF processorscontrol the operation of the RF transceivers and process the RFidentification signals received through the antennas and transceivers.

In some instances, imaging-based inventory scans of the tool storagesystem 300 have the disadvantage that they cannot distinguish betweenphysically identical (or similar) tools. For example, an imaging-basedinventory scans may be unable to distinguish between two identicalwrenches. In order to address this deficiency, the tool storage system300 can rely on a tag-based system to distinguish between differenttools. The tag-based system relies on a tag provided on a tool touniquely identify the tool. Specifically, the tag can encode anidentifier unique to the tool, such that the unique tool (e.g., aparticular torque wrench, from among a plurality of torque wrenches ofthe same model and type) can be identified from reading the tag. Inparticular, the information encoded in the tag is generally unique tothe tool such that it can be used to distinguish between two tools thatare of a same type, same model, same age, same physical appearance, etc.

In one example, the tag-based system includes RFID tags placed on toolsand encoding the identifiers unique to each tool.

In another example, the tag-based system includes visible tags placed ontools and encoding the identifiers unique to each tool. The visible tagscan be placed on the tools so as to be visible to the image sensingsystem of the tool storage system 300. Examples of tags are shown inFIGS. 4A-4C. For example, tags can include a tag 401 a having a visiblepattern thereon for recognition by an imaging-based sensing subsystem ora tag 401 b disposed on or in a tool having an RFID-readable (or otherwirelessly-readable) code encoded therein. Combination tags includingboth visible and RFID-readable codes may also be used.

While a single tag (401 a, 401 b) is shown as being placed on a tool inthe illustrative examples of FIGS. 4B and 4C, multiple tags may beplaced on a tool. For example, tags can be placed on multiple differentfaces of a tool to ensure that at least one tag is upward facing towardsan imaging-based sensing subsystem (e.g., towards a camera 310)irrespective of the orientation in which the tool is placed in the toolstorage system 300. The multiple tags located on a given tool may beidentical to each other; alternatively, the multiple tags may bedifferent from each other with tag data for each of the multiple tagsbeing associated with the tool in the stored tool data used by the toolstorage system 300.

The tags may be formed of a polycarbonate, polyester, or other suitablematerial, and may have an adhesive backing so as to adhere to the toolsthey are mounted on. In one example, the information encoded in the tagsis encoded using differently colored bands or stripes such as thoseshown in the illustrative example of FIG. 4A (in which white, purple,red, black, dark blue, light blue, green, and yellow stripes are shown).Both primary colors and/or blended colors may be used. Each color stripeon the tag equates to a number (or alphanumeric character) and thecombination of colors creates a code. In general, the first and laststripes represent start and stop codes. The start and stop codes cancorresponds to particular respective colors. In one example, the startcode can be a stripe of one particular color (e.g., cyan) and the stopcode can be a stripe of another particular color (e.g., green), and alltags may start with the same start code and end with the same end code.In some examples, adjacent stripes are always of different colors (e.g.,no color can be located directly adjacent to itself on a tag). In theembodiment depicted in FIG. 4A, all stripes have a same length andwidth; in order embodiments, adjacent stripes may have different lengthsand/or widths.

For durability, the tags can include multiple layers including a firstlayer (base layer) formed of polycarbonate/polyester or other suitablematerial, a second layer including color coded ink, a third layerincluding white ink, a fourth layer including adhesive, and a fifthlayer including a peel off backing that is removed when the tag isadhesively applied to a tool or other object.

In one example, the tag uses six different colors to establish the codes(e.g., six stripes of different colors in addition to the start code andstop code stripes). In this example, the total number of different codesthat can be encoded on tags depends on the number of stripes provided onthe tags. The tags may be designed with a restriction that no same colorcan be present in side to side adjacent stripes, for example to improvereadability of the tags by the image sensing system. With such arestriction, 13,021 discrete tag codes can be formed using six digitcodes (and six different colors) and 65,104 discrete tag codes can beformed using seven digit codes (and six different colors). Largernumbers of discrete tag codes can be obtained if the restriction isremoved to allow same color stripes to be disposed adjacent to eachother.

In other examples, different numbers of stripes/digits and/or differentnumbers of different colors can be used to generate larger or smallernumbers of discrete tag codes. For example, FIGS. 4A and 4B showillustrative examples in which eight stripes or bands are used (and inwhich eight different colors are used).

Additionally, tag sizes can vary depending on a distance of the tagsfrom the imaging device and/or the sizes of tools. For example, largetags (with wide colored stripes/bands) can be provided for large toolsand/or tools provided in lower drawers of a tool storage system 300(e.g., drawers located relatively far from the imaging devices 310 inthe example of FIG. 3), while smaller tags (with narrower coloredstripes/bands) can be provided for smaller tools and tools provided inupper drawers (e.g., drawers located closer to the imaging devices 310).

In general, all of the stripes or bands on a tag have the same width aseach other. The stripes or bands on different tags may have the samewidth as each other or, alternatively, stripes or bands on differenttags may have different widths (e.g., as described above, larger tagsmay have wider stripes or bands, while smaller tags may have narrowerstripes or bands).

In order for the tool storage system 300 to make use of the tagsdisposed on tools (and/or other objects) stored in the tool storagesystem 300, the tool data used by the tool storage system 300 todetermine inventory conditions should include the tag data. In thisregard, the tool data should be created or updated to include the uniqueidentifier encoded in each tag and to associate the appropriate toolwith each unique identifier.

In general, tool data stored by the tool storage system 300 is used todetermine inventory conditions of objects/tools stored in the toolstorage system 300. In an image-based tool storage system 300 that usesan image sensing system to determine the inventory condition (e.g.,presence or absence) of objects and tools stored in the system 300, thetool data can be generated through the use of files such as text files.In operation, the database of tool data used by the system 300 isgenerated based on object related data that is entered into the systemmemory and database through the use of a process in which a data file(e.g., a text file) is created which defines specific object/toolattributes. The data file is read by a computer program during initialset up of the automated tool storage and control system 300 and datafrom the file is loaded into the appropriate fields of the tool datadatabase to provide for proper operation of the system 300.

The data provided in the data file (e.g., text file) and loaded in thetool data database can include, for example, information associatingwith each entry in the data a customer (e.g., customer name or uniqueidentifier), a storage device name (e.g., identifying a particular toolbox or other storage device in which the tool or object is to bestored), a drawer identifier (e.g., identifying a particular drawer ofthe tool box or other storage device in which the tool or object is tobe stored), a silhouette name, location, and shape identifier (e.g., atool silhouette on the basis of which the system determines presence orabsence of the tool from storage), an object description (e.g., a namefor the tool), and information on channels and/or holes (e.g., channelsand holes contiguous with object or tool storage locations and designedto enable users' fingers to grasp the objects or tools from the storagelocations).

Typically, the information in the data files does not includeinformation on the tags described above or on the unique identifiersencoded therein. The tag information may not be included in the datafiles because the tags (with their identifying codes/data) may only beapplied to the stored objects/tools after the system database ispopulated with the information from the data files, and the identifyingcodes/data from the tags thus cannot generally be included in the datafiles read-in by the system. Moreover, the data file data may beprovided by a manufacturer of the tool storage system 300 or amanufacturer of the tools, while the tags may be applied by an end userbased on the particular tools to be used in the storage device, and themanufacturer may thus generally not know what identifying codes/data isto be associated with each object/tool in the data file.

As a result, the tag information generally needs to be provided to andloaded into the tool data database of the tool storage system 300separately from the data files. The process for manually associating taginformation with each set of tool data stored in the database is slowand tedious. As a result, an automated method to enter the identifyinginformation from the tag into the tool data database of the tool controland storage system 300 and associate the tag information withpre-existing object/tool related data of the database is needed.

Moreover, if a tag must be replaced due to loss, damage, normal wear andtear, or other reason, an automated method to replace the existing tagidentifying data stored in the tool data database with new data for thenew replacement tag and to associate the new data with the appropriateobject does not currently exist.

This disclosure thus provides an automated process to enter theidentifying information from the tag into the tool data database of thetool control and storage system 300 and associate the tag informationwith pre-existing object related data. In addition, the disclosure alsoprovides a quick and easy automated way to update the database andassociate data from a new tag with the appropriate object stored in thetool control and storage system 300.

In operation, the automated process for updating the tool data databasecan be performed in a tool control and storage system 300 that includeselectronic and software means to read and utilize text data contained ina data file (e.g., a text file) to populate the tool data databasefields with tool data. The data can include, but is not limited to, anobject identifier; a customer identifier or name; a storage device name;a drawer identifier; a silhouette name, location, and shape identifier;an object description; one or more channel definitions; one or more holedefinitions; and/or other appropriate information.

The system also includes program instructions for causing the toolstorage system 300 to operate in a tool/drawer training mode and causethe system 300 to read image data obtained by the image sensing system(e.g., at least one camera) and correlate the image data with the datafrom the data file (e.g., text file) that has been stored in thedatabase.

The system then uses the correlated data to complete the steps in thetool training process for silhouette training, for absence signatureacquisition, and/or for presence signature acquisition.

FIG. 5 is a simplified block diagram showing steps of a method 500 fortool training. In accordance with method 500, to automatically add taginformation from tag to the tool data database of the system 300, stepsmay involve a step 501 for attaching a tag to an item (e.g., a tool orother objects) to be stored in a pocket or other storage location of thetool storage system 300. In turn, the tool training process in initiatedin step 503. The tool training process can be initiated by a user by,for example, selecting a tool training process activation icon on a userinterface 305 of the tool storage system 300. In one example, the usermay select an option to initiate a tool training process for alltools/objects stored in a drawer, shelf, compartment, or tool storagesystem (e.g., by selecting the drawer, shelf, compartment, or the likeon the user interface 305), or select an option to initiate a tooltraining process for one or more particular tools in the tool storagesystem (e.g., by selecting the one or more particular tools or objectson the user interface 305).

The tool training process conducts silhouette training with no objectsin the tool storage locations in step 505. Prior to performing thesilhouette training, the system 300 may thus instruct a user to removefrom the storage locations those tools or other objects subject totraining. The silhouette training can include the tool storage system300 activating its image sensing system to scan all storage locations ofthe system and detect silhouettes of the storage locations when noobjects are stored therein. In one example, the tool storage system 300may instruct the user to open and close the drawer(s) subject totraining in order to enable the image sensing system to capture image(s)of the storage locations. The tool storage system 300 can then performimaging processing to identify silhouettes of tool storage locations inthe captured images; for example, an edge detection algorithm may beused to detect edge of the tool storage locations in the image. In thecase of a tool training process for all tools/objects, the tool storagesystem 300 then determines, based on pattern matching between thesilhouettes of tool storage locations in the captured images andsilhouettes of tool storage locations stored in memory of the toolstorage system 300, an alignment between the silhouettes. In the case ofa tool training process for one or more particular tools, the toolstorage system 300 determines, based on an alignment between silhouettesof tool storage locations for the one or more particular tools in thecaptured image(s) and stored in memory, an alignment parameter betweenthe tool storage locations and the image sensing system. The alignmentparameter may characterize the positions of the storage locations withinthe storage drawers or shelves relative to the imaging sensing system,including characterizations of the positions and rotational alignment ofthe storage locations within the storage drawers or shelves and relativeto the field of view of the imaging sensing system. The determinedalignment parameter is then used by the tool training system 300 toidentify the expected locations of storage locations and stored tools inimages captured by the image sensing system in subsequent operation ofthe system 300.

The tool training process then conducts a tool absence training in step507 to record color attributes (or other attributes) of the emptystorage locations (or pockets). The tool absence training can includethe tool storage system 300 activating its image sensing system to scanall storage locations of the system to detect color attributes of thestorage locations when no objects are stored therein. Alternatively, thesystem 300 can use the image(s) captured during the silhouette training.In the tool absence training step, the tool storage system 300identifies, for each storage location (e.g., each storage locationidentified through the silhouette training), the color, color signature,or other image attributes of the storage location when no tool or objectis located in the storage location. In the case of a tool trainingprocess for all tools/objects, the tool absence training is performedfor all storage locations; in the case of a tool training process forone or more particular tools, the tool absence training is performed forthose storage locations associated with the one or more particulartools. The tool storage system 300 then stores the color, colorsignature, or other image attributes of the storage location when notool or object is located in the storage location for use in futuredeterminations of tool presence or absence.

In turn, the tool presence training process conducts tool presencetraining in step 509 with tool(s) in the storage locations (or pockets).As part of performing the presence training, the system 300 may instructa user to place in the storage locations those tools or other objectssubject to training. The tool presence training can include the toolstorage system 300 activating its image sensing system to scan allstorage locations of the system and detect image attributes of thestorage locations when the objects/tools are stored therein. In oneexample, the tool storage system 300 may instruct the user to open andclose the drawer(s) subject to training in order to enable the imagesensing system to capture image(s) of the storage locations. The toolpresence training can include performing three sequential scans toensure accuracy and consistency of the data captured during each of thethree scans. The system 300 may instruct the user to remove and replacethe tools subject to training between the sequential scans and, ifappropriate, to rotate the tools in the storage locations between thesequential scans (e.g., in situations in which tools can be insertedinto the storage locations in more than one orientation). The toolpresence training can result in the system recording image attributes orcolor attributes of storage locations (e.g., pockets) with tool(s)present. Specifically, in the tool presence training step, the toolstorage system 300 identifies, for each storage location (e.g., eachstorage location identified through the silhouette training), the color,color signature, or other image attributes of the storage location(s)when the tool(s) or object(s) are present and located in the storagelocation(s). In the case of a tool training process for alltools/objects, the tool presence training is performed for all storagelocations; in the case of a tool training process for one or moreparticular tools, the tool presence training is performed for thosestorage locations associated with the one or more particular tools. Thetool training system 300 then stores the color, color signature, orother image attributes of the storage location when a tool or object islocated in the storage location for use in future determinations of toolpresence or absence.

If a tag (e.g., a tag including color-coded stripes or bands) is presenton any tool or object during the tool presence training, the system 300is operative to recognize the tag as a coded tag in step 511. Inparticular, the system may recognize the tag by identifying a tag startcode and a tag stop code in an image captured by the image sensingsystem during the tool presence training, and by identifying anappropriate number of colored stripes (e.g., six stripes, or sevenstripes) between the start code and stop code stripes. The system thendetects and determines the tag code by identifying the color (or otherattribute) of each strip and translating the sequence of identifiedcolors into a sequence of corresponding alphanumeric characters,validates the tag code to ensure that the determined tag code confirmsto an appropriate format, and creates an association in the tool datadatabase associating the identified code data with the object datapreviously entered in the database through the use of the text file. Theidentified code data may be associated with the object data based on thelocation of the tag in the captured image; for example, the location ofthe tag may be compared with positions of identified silhouettes toidentify a silhouette with which to associate the code data, and thecode data may in turn be associated with the object data correspondingto the identified silhouette.

In examples in which the tool storage system 300 forms part of networkedsystem, the tag data is initially stored in the tool data databasestored locally by the system 300 and is later copied to a correspondingdatabase stored in a connected server (step 513).

The foregoing description of the process for automatically adding taginformation to the tag data database indicates that the silhouettetraining (step 505) and tool absence training (step 507) are performedwhen no objects are stored in storage locations of the tool storagesystem 300. More generally, however, the process can be performed to addtag information for a limited number of object(s) (e.g., one object, ortwo or more objects, but not necessarily all objects stored in thesystem 300). In such a case, the silhouette training (step 505) and toolabsence training (step 507) are performed such that those storagelocations associated with (or configured to store) the limited number ofobject(s) for which training is being performed are empty of storageobjects. During the silhouette training (step 505) and tool absencetraining (step 507), the tool storage system 300 can identify whichstorage location(s) are empty (or otherwise do not have objects storedtherein) based on the currently stored tool data of the database, andthe system 300 can then perform the silhouette training (step 505) andtool absence training (step 507) on the identified storage location(s).In turn, the tool presence training (step 509) is then performed on thesame set of identified storage location(s) such that tag data can beassociated with each of the tools (and storage location(s)) in step 511.

The tool storage system 300 can similarly be used to update taginformation stored in the database for example in cases in whichreplacement of a lost, worn, or damaged tag is performed. In such asituation, a user can remove the tag from the object if available andreplace the tag with a new tag. In turn, the full tool training processas described above can be conducted.

Alternatively, the user can remove the tag from the object if availableand replace the tag with the new tag. The user can then conduct anindividual tool training process in which the user selects the tool forwhich training is to be performed (e.g., using a user interface of thetool storage system 300). Once the user has selected the tool, thesystem 300 conducts, silhouette training (e.g., 505) with no object inthe storage location or pocket associated with the selected tool. Thesystem 300 further conducts tool absence training (e.g., 507) to recordcolor attributes of the empty storage location or pocket. In turn, thesystem 300 instructs the user to place the tool in the storage locationand the system then conducts tool presence training (e.g., 509) with theselected tool in the storage location or pocket. The tool presencetraining can include scanning the storage location or pocket three timesand recording color attributes of the storage location or pocket withthe tool present. The silhouette, tool absence, and tool presencetraining steps can be performed irrespective of whether other storagelocations or pockets (e.g., storage locations or pockets other than thatof the selected tool) are occupied or unoccupied. The tool presencetraining further includes determining whether a color tag is present onany tool or object (e.g., 511) in images captured during the toolpresence training and, if the determination indicates that a color tagis present, recognizing the color tag as a coded tag. The tag code isthen determined and validated, and the system then associates in thetool data database the identified/validated code data with the objectdata previously entered in the database through the use of the textfile.

As noted above, the tag data is initially stored in the database of thetool storage system 300 and is then copied to a server database inembodiments in which a server database is used (e.g., 513).

Since serialized tool data is now associated with the tool and can beidentified through use of the tag, the tool with a tag applied can bestored in any identical pocket and the tool data will follow the tool.

In operation, the tool storage system 300 can use the stored tool datato determine presence or absence of tools or other objects in storagelocations of the system. For example, the system 300 may capture animage of storage location(s) using the image sensing device and maycompare the captured image (or a portion thereof determined tocorrespond to a storage location) to the stored image attributes storedduring the tool absence training and tool presence training. Based onthe comparison, the system 300 identifies the stored image that has theclosest match to the captured image and determines presence or absenceof the object or tool based on whether the closest match is to a storedimage (or image attribute) associated with the presence or with theabsence training. The system 300 further determines whether a color tagis present on any object or tool determined to be present based on thecaptured image, determines a tag code of the color tag, and therebydetermines the identity of the particular object or tool present byretrieving object or tool data associated with the determined tag code.

FIGS. 6 and 7 provide functional block diagram illustrations of generalpurpose computer hardware platforms. FIG. 6 illustrates a network orhost computer platform, as may typically be used to implement a server(e.g., 361). FIG. 7 depicts a computer with user interface elements, asmay be used to implement a tool storage system 300 including a userinterface 305, although the computer of FIG. 7 may also act as a serverif appropriately programmed. It is believed that those skilled in theart are familiar with the structure, programming and general operationof such computer equipment and as a result the drawings should beself-explanatory.

A server, for example, includes a data communication interface forpacket data communication. The server also includes a central processingunit (CPU), in the form of one or more processors, for executing programinstructions. The server platform typically includes an internalcommunication bus, program storage and data storage for various datafiles to be processed and/or communicated by the server, although theserver often receives programming and data via network communications.The hardware elements, operating systems and programming languages ofsuch servers are conventional in nature, and it is presumed that thoseskilled in the art are adequately familiar therewith. Of course, theserver functions may be implemented in a distributed fashion on a numberof similar platforms, to distribute the processing load.

Unless otherwise stated, all measurements, values, ratings, positions,magnitudes, sizes, and other specifications that are set forth in thisspecification, including in the claims that follow, are approximate, notexact. They are intended to have a reasonable range that is consistentwith the functions to which they relate and with what is customary inthe art to which they pertain.

The scope of protection is limited solely by the claims that now follow.That scope is intended and should be interpreted to be as broad as isconsistent with the ordinary meaning of the language that is used in theclaims when interpreted in light of this specification and theprosecution history that follows and to encompass all structural andfunctional equivalents. Notwithstanding, none of the claims are intendedto embrace subject matter that fails to satisfy the requirement ofSections 101, 102, or 103 of the Patent Act, nor should they beinterpreted in such a way. Any unintended embracement of such subjectmatter is hereby disclaimed.

Except as stated immediately above, nothing that has been stated orillustrated is intended or should be interpreted to cause a dedicationof any component, step, feature, object, benefit, advantage, orequivalent to the public, regardless of whether it is or is not recitedin the claims.

It will be understood that the terms and expressions used herein havethe ordinary meaning as is accorded to such terms and expressions withrespect to their corresponding respective areas of inquiry and studyexcept where specific meanings have otherwise been set forth herein.Relational terms such as first and second and the like may be usedsolely to distinguish one entity or action from another withoutnecessarily requiring or implying any actual such relationship or orderbetween such entities or actions. The terms “comprises,” “comprising,”or any other variation thereof, are intended to cover a non-exclusiveinclusion, such that a process, method, article, or apparatus thatcomprises a list of elements does not include only those elements butmay include other elements not expressly listed or inherent to suchprocess, method, article, or apparatus. An element proceeded by “a” or“an” does not, without further constraints, preclude the existence ofadditional identical elements in the process, method, article, orapparatus that comprises the element.

The Abstract of the Disclosure is provided to allow the reader toquickly ascertain the nature of the technical disclosure. It issubmitted with the understanding that it will not be used to interpretor limit the scope or meaning of the claims. In addition, in theforegoing Detailed Description, it can be seen that various features aregrouped together in various embodiments for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter lies in less than allfeatures of a single disclosed embodiment. Thus the following claims arehereby incorporated into the Detailed Description, with each claimstanding on its own as a separately claimed subject matter.

While the foregoing has described what are considered to be the bestmode and/or other examples, it is understood that various modificationsmay be made therein and that the subject matter disclosed herein may beimplemented in various forms and examples, and that the teachings may beapplied in numerous applications, only some of which have been describedherein. It is intended by the following claims to claim any and allapplications, modifications and variations that fall within the truescope of the present teachings.

What is claimed is:
 1. An automated asset management system comprising:a plurality of storage locations for storing objects; an image-basedsensing system comprising at least a camera configured to generateimages used to determine presence or absence of objects configured to bestored in the plurality of storage locations; a database storing datarelating to the objects configured to be stored in the plurality ofstorage locations, wherein the database stores data sufficient to enablethe asset management system to determine the presence or absence of theobjects from the storage locations based on the images generated by theimage-based sensing system; a processor; and a non-transitory machinereadable recording medium storing program instructions which, whenexecuted by the processor, cause the processor to perform a tooltraining process for automatically storing in the database a uniqueidentifier encoded on a tag of an object by: performing using theimage-based sensing system a first scan of the storage locations while aparticular storage location associated with a particular object subjectto the tool training is empty, and storing an image attribute of theparticular storage location while the particular storage location isempty, performing using the image-based sensing system a second scan ofthe storage locations while the particular storage location associatedwith the particular object subject to the tool training is occupied bythe particular object, and storing an image attribute of the particularstorage location while the particular object is present, determining,based on an image captured during the second scan, whether a tagencoding a unique identifier is present on the particular object, andupdating the database storing data relating to the objects configured tobe stored in the plurality of storage locations of the asset managementsystem to include, in association with stored data relating to theparticular object, the unique identifier of the tag determined to bepresent on the particular object.
 2. The automated asset managementsystem of claim 1, wherein the processor determines presence of the tagencoding the unique identifier on the particular object by detecting astart code and a stop code in the image captured by the image-basedsensing system during the second scan.
 3. The automated asset managementsystem of claim 1, wherein the processor determines presence of the tagencoding the unique identifier on the particular object system bydetecting the tag in a portion of the image associated with theparticular object.
 4. The automated asset management system of claim 3,wherein the tag includes a plurality of adjacent stripes havingdifferent colors, and the processor is configured to determine theunique identifier encoded in the tag based on the sequence of colors inthe adjacent stripes.
 5. The automated asset management system of claim1, wherein the processor determines presence of a tag encoding a uniqueidentifier on the particular object by performing steps of: detectingthe tag at a location associated with the particular object in the imagecaptured by the image-based sensing system; identifying, in the detectedtag, colors of adjacent stripes having different colors; and translatingthe identified colors into corresponding alphanumeric characters,wherein the updating of the database includes storing data including thetranslated alphanumeric characters corresponding to the identifiedcolors of the tag.
 6. The automated asset management system of claim 5,wherein the detecting of the tag comprises detecting, in the imagecaptured by the image-based sensing system, a start code and a stop codeassociated with a tag, and identifying a portion of the image locatedbetween locations of the start code and the stop code as the detectedtag.
 7. The automated asset management system of claim 1, wherein theprocessor is further configured to determine the presence or absence ofthe particular object in the plurality of storage locations byperforming steps of: performing a third scan of the storage locationsusing the image-based sensing system; determining the presence orabsence of the particular object in at least one of the plurality ofstorage locations based on whether image attributes of an image capturedin the third scan are a closest match to image attributes of imagescaptured in the second or first scans, respectively.
 8. The automatedasset management system of claim 1, wherein the processor is furtherconfigured to: based on a first image generated by the image-basedsensing system during the first scan, identify silhouettes of storagelocations in the first image and determine an alignment between theidentified silhouettes and expected locations of silhouettes stored inthe automated asset management system, wherein the determined alignmentis stored in the database storing data relating to the objectsconfigured to be stored in the plurality of storage locations of theasset management system.
 9. The automated asset management system ofclaim 1, wherein the processor provides an instruction to a user of theasset management system to ensure that the particular object is absentfrom the particular storage location of the asset management systemprior to performing the first scan, and the processor provides aninstruction to the user of the asset management system to place theparticular object in the particular storage location of the assetmanagement system prior to performing the second scan.
 10. The automatedasset management system of claim 1, wherein the processor determines,based on an image obtained in the first scan, a color characteristic ofthe determined storage location when no object is present therein, andthe processor determines, based on an image obtained in the second scan,an image attribute of the determined storage location when the object ispresent therein.
 11. The automated asset management system of claim 1,wherein the processor provides an instruction to a user of the assetmanagement system to affix a tag to the particular object prior toperforming the second scan.
 12. The automated asset management system ofclaim 1, wherein the processor updates the database storing datarelating to the objects to replace a previously stored identifierassociated with the particular object with the unique identifier of thetag determined to be present on the particular object.
 13. The automatedasset management system of claim 1, wherein the processor updates thedatabase storing data relating to the objects by creating an entryassociated with the data relating to the particular object determined tobe present and including the unique identifier of the tag determined tobe present on the particular object.
 14. A method for automaticallystoring, in a database of an automated asset management system having aplurality of storage locations for storing objects, a unique identifierencoded on a tag of an object, the method comprising: performing, usingan image-based sensing system comprising at least a camera configured togenerate images used to determine presence or absence of objectsconfigured to be stored in the plurality of storage locations of theasset management system, a first scan of the plurality of storagelocations while a particular storage location associated with aparticular object subject to tool training is empty; storing in thedatabase an image attribute of the particular storage location while theparticular storage location is empty; performing, using the image-basedsensing system, a second scan of the storage locations while theparticular storage location associated with the particular objectsubject to the tool training is occupied by the particular object;storing in the database an image attribute of the particular storagelocation while the particular object is present; determining, based onan image generated by the image-based sensing system during the secondscan, whether a tag encoding a unique identifier is present on theparticular object; and updating the database of the asset managementsystem storing data relating to the objects configured to be stored inthe plurality of storage locations to include, in association withstored data relating to the particular object, the unique identifier ofthe tag determined to be present on the particular object, wherein theimage attributes stored in the database are sufficient to enable theasset management system to determine the presence or absence of theobjects from the storage locations based on the images generated by theimage-based sensing system.
 15. The method of claim 14, wherein thedetermining whether a tag encoding a unique identifier is present on theparticular object comprises identifying, in the image generated by theimage-based sensing system during the second scan, a portion of theimage that includes the particular object, and determining whether thetag is present in the identified portion of the image.
 16. The method ofclaim 15, wherein the presence of the tag encoding the unique identifieron the particular object is determined by detecting a start code and astop code in the identified portion of the image captured by theimage-based sensing system during the second scan.
 17. The method ofclaim 16, wherein the tag includes a plurality of adjacent stripeshaving different colors, and the method further comprises determiningthe unique identifier encoded in the tag based on the sequence of colorsin the adjacent stripes.